AIMC Topic: Colon
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Discriminative error prediction network for semi-supervised colon gland segmentation.
Medical image analysis
Apr 22, 2022
Pixel-wise error correction of initial segmentation results provides an effective way for quality improvement. The additional error segmentation network learns to identify correct predictions and incorrect ones. The performance on error segmentation ...
Protection against ulcerative colitis and colorectal cancer by evodiamine via anti‑inflammatory effects.
Molecular medicine reports
Apr 1, 2022
Evodiamine (Evo) is an alkaloid that can be extracted from the berry fruit and has been reported to exert various pharmacological effects, such as antidiarrheal, antiemetic and antiulcer effects. , the potential effects of Evo were investigated in a...
Deep Learning Analysis of Histologic Images from Intestinal Specimen Reveals Adipocyte Shrinkage and Mast Cell Infiltration to Predict Postoperative Crohn Disease.
The American journal of pathology
Mar 28, 2022
Most patients with Crohn disease (CD), a chronic inflammatory gastrointestinal disease, experience recurrence despite treatment, including surgical resection. However, methods for predicting recurrence remain unclear. This study aimed to predict post...
Colon tissue image segmentation with MWSI-NET.
Medical & biological engineering & computing
Jan 19, 2022
Developments in deep learning have resulted in computer-aided diagnosis for many types of cancer. Previously, pathologists manually performed the labeling work in the analysis of colon tissues, which is both time-consuming and labor-intensive. Result...
Economizing on a 12 mm port incision site: modification of robotic bowel stapling technique in Da Vinci X/Xi left colonic resections-the modified Norfolk and Norwich robotic stapling technique.
Journal of robotic surgery
Jan 12, 2022
The modified Norfolk and Norwich technique allows to replace a 12 mm port incision site by an 8 mm one, therefore reducing potential postoperative complications linked to 12 mm incisions by robotically stapling through the routinely placed suprapubic...
Accurate diagnosis of atopic dermatitis by combining transcriptome and microbiota data with supervised machine learning.
Scientific reports
Jan 7, 2022
Atopic dermatitis (AD) is a common skin disease in childhood whose diagnosis requires expertise in dermatology. Recent studies have indicated that host genes-microbial interactions in the gut contribute to human diseases including AD. We sought to de...
Detecting colon polyps in endoscopic images using artificial intelligence constructed with automated collection of annotated images from an endoscopy reporting system.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Nov 30, 2021
BACKGROUND: Artificial intelligence (AI) has made considerable progress in image recognition, especially in the analysis of endoscopic images. The availability of large-scale annotated datasets has contributed to the recent progress in this field. Da...
Automated recognition of objects and types of forceps in surgical images using deep learning.
Scientific reports
Nov 19, 2021
Analysis of operative data with convolutional neural networks (CNNs) is expected to improve the knowledge and professional skills of surgeons. Identification of objects in videos recorded during surgery can be used for surgical skill assessment and s...
Smart surgical sutures using soft artificial muscles.
Scientific reports
Nov 17, 2021
Wound closure with surgical sutures is a critical challenge for flexible endoscopic surgeries. Substantial efforts have been introduced to develop functional and smart surgical sutures to either monitor wound conditions or ease the complexity of knot...
Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study.
The Lancet. Digital health
Oct 19, 2021
BACKGROUND: Determining the status of molecular pathways and key mutations in colorectal cancer is crucial for optimal therapeutic decision making. We therefore aimed to develop a novel deep learning pipeline to predict the status of key molecular pa...
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